Variance Reduction Techniques

Variance reduction techniques are methods used to improve the accuracy of simulation or statistical estimates by minimizing the variability or noise in the results. They help produce more reliable outcomes with fewer samples, saving time and computational resources. Common techniques include using control variates, antithetic variates, or importance sampling, which intelligently modify or guide the sampling process. This allows analysts to achieve precise estimates more efficiently, especially in complex systems or stochastic models, by focusing on the most informative data and reducing the randomness that can cloud the true signal.